Geoffroy Delamare

And it’s out!! Check out the newest paper from our lab on how chromatin plasticity predetermines neuronal selection for memory trace formation | science.org/doi/10.1126/sc… 🧵

📢 Job alert 📢 We are recruiting a PhD student! 💻 Apply and join my lab at @KISNeuro 🧠 Deadline: August 25 Apply here: jobbnorge.no/en/available-j…

This work was done is collaboration between @ClopathLab, @denisejcai and @mysteriousjoe_, thanks a lot to the authors!

Finally, we used an output decoder to show that the memory content is preserved during drift. This works through local Hebbian learning that allows the output neuron to “track” the drifting ensemble. 4/5

New paper! In memory and sensorial systems, neural ensembles tend to drift across several days, but the underlying mechanisms are unclear. We modelled excitability in a recurrent neural network to explain drift and time-stamping of neural ensembles. elifesciences.org/articles/88053 1/5

Interested in how excitability can promote representational drift of memories? Check out our new paper with @geoffroy_del, Yosif Zaki and @denisejcai elifesciences.org/articles/88053

Out now in PNAS! Do you want to predict neuronal responses better than with deep neural network models? We show how Gaussian Processes can do this even with high-dimensional natural stimuli and little data. pnas.org/doi/10.1073/pn…

🚨#tweetprint time! 🚨🎉 📝 tinyurl.com/nonlinearmanif… We tested the hypothesis that due to the nonlinear responses of single neurons and the intricate connectivity of brain circuits, neural manifolds would be nonlinear. (1/17)

🚨Tweetprint time! 🚨 We studied how de novo motor learning alters the underlying neural activity & affects motor adaptation using RNNs 📜 t.ly/vSLo Special thanks to coauthors @mattperich @PresNCM @JAlGallego @ClopathLab Pls read 🧵 + RT! 1/n

New preprint of the @ClopathLab in collaboration with @mysteriousjoe_ and @denisejcai! we propose a model where fluctuations of excitability induce drift of neural ensembles, leading to "time-stamping" of memories biorxiv.org/content/10.110…

@StephaneDeny @RetinaGeek @InstVisionParis They probably do not reflect the actual architecture of the network, that is why they are not present in the time-dependent framework which integrates the statistics of the stimulus in the TD biases h[t].

@StephaneDeny @RetinaGeek @InstVisionParis We thought they could arise due to shared noise from the photoreceptors, which anti-correlates ON and OFF cells over small distance for the checkerboard stimulus and long distances for the full-field stimulus.

Paper is out! Using maximum entropy models in statistical physics, we modelled the dynamics of large networks of multiple neuron types, from recordings of retinal ganglion cells performed by @StephaneDeny and @RetinaGeek @InstVisionParis mdpi.com/2673-9984/5/1/…

Registration is now open!🎉Link below👇 We're so excited to invite all of you to Faro in May! Come and present your work to fellow PhD and early-career neuroscientists as posters, flash presentations, and longer-format talks! 🎙 fens.org/news-activitie… @FENSRM @FENSorg

🚨New preprint! we have built a computational model of memory engrams, combining intrinsic neural excitability and synaptic plasticity, and discussed how both features regulate memory allocation and linking: biorxiv.org/content/10.110…

Intrinsic neural excitability induces time-dependent overlap of memory engrams biorxiv.org/cgi/content/sh… #biorxiv_neursci